OpenIntro Statistics
Diez, David M.
OpenIntro Statistics David Diez - Fourth Edition - 1 online resource - Open textbook library. .
1. Introduction to data. -- 2. Summarizing data. -- 3. Probability. -- 4. Distributions of random variables. -- 5. Foundations for inference. -- 6. Inference for categorical data. -- 7. Inference for numerical data. -- 8. Introduction to linear regression. -- 9. Multiple and logistic regression.
OpenIntro Statistics covers a first course in statistics, providing a rigorous introduction to appliedstatistics that is clear, concise, and accessible. This book was written with the undergraduate levelin mind, but it's also popular in high schools and graduate courses.We hope readers will take away three ideas from this book in addition to forming a foundationof statistical thinking and methods. • Statistics is an applied field with a wide range of practical applications.• You don't have to be a math guru to learn from real, interesting data.• Data are messy, and statistical tools are imperfect. But, when you understand the strengthsand weaknesses of these tools, you can use them to learn about the world.
In English.
Mathematics--Textbooks
Applied mathematics--Textbooks
QA1 QA37.3
OpenIntro Statistics David Diez - Fourth Edition - 1 online resource - Open textbook library. .
1. Introduction to data. -- 2. Summarizing data. -- 3. Probability. -- 4. Distributions of random variables. -- 5. Foundations for inference. -- 6. Inference for categorical data. -- 7. Inference for numerical data. -- 8. Introduction to linear regression. -- 9. Multiple and logistic regression.
OpenIntro Statistics covers a first course in statistics, providing a rigorous introduction to appliedstatistics that is clear, concise, and accessible. This book was written with the undergraduate levelin mind, but it's also popular in high schools and graduate courses.We hope readers will take away three ideas from this book in addition to forming a foundationof statistical thinking and methods. • Statistics is an applied field with a wide range of practical applications.• You don't have to be a math guru to learn from real, interesting data.• Data are messy, and statistical tools are imperfect. But, when you understand the strengthsand weaknesses of these tools, you can use them to learn about the world.
In English.
Mathematics--Textbooks
Applied mathematics--Textbooks
QA1 QA37.3